package com.codejiwei.flink.sql;

import com.codejiwei.flink.entity.WaterSensor;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.types.Row;

import static org.apache.flink.table.api.Expressions.$;

/**
 * @author jiwei
 * @description
 * @date 2023/5/25 16:48
 */
public class Flink_Table_BaseUse {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(2);
        DataStreamSource<WaterSensor> waterSensorStream =
                env.fromElements(new WaterSensor("sensor_1", 1000L, 10),
                        new WaterSensor("sensor_1", 2000L, 20),
                        new WaterSensor("sensor_2", 3000L, 30),
                        new WaterSensor("sensor_1", 4000L, 40),
                        new WaterSensor("sensor_1", 5000L, 50),
                        new WaterSensor("sensor_2", 6000L, 60));
        //1. 创建表的执行环境
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
        //2. 创建表，流转换成动态表，表的字段名从pojo中属性名自动抽取
        Table inputTable = tableEnv.fromDataStream(waterSensorStream);
        //3. 对动态表进行查询
        Table resultTable = inputTable.where($("id").isEqual("sensor_1"))
                .select($("id"), $("ts"), $("vc"));
        tableEnv.toDataStream(resultTable, Row.class).print();
//        tableEnv.toChangelogStream(resultTable).print();


        env.execute();

    }
}
